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Using Full and Partial Unmixing Algorithms to Estimate the Inundation Extent of Small, Isolated Stock Ponds in an Arid Landscape

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Abstract

Many natural wetlands around the world have disappeared or been replaced, resulting in the dependence of many wildlife species on small, artificial earthen stock ponds. These ponds provide critical wildlife habitat, such that the accurate detection of water and assessment of inundation extent is required. We applied a full (linear spectral mixture analysis; LSMA) and partial (matched filtering; MF) spectral unmixing algorithm to a 2007 Landsat 5 and a 2014 Landsat 8 satellite image to determine the ability of a time-intensive (i.e., more spectral input; LSMA) vs. a more efficient (less spectral input; MF) spectral unmixing approach to detect and estimate surface water area of stock ponds in southern Arizona, USA and northern Sonora, Mexico. Spearman rank correlations (rs) between modeled and actual inundation areas less than a single Landsat pixel (< 900 m2) were low for both techniques (rs range = 0.22 to 0.62), but improved for inundation areas >900 m2 (rs range = 0.34 to 0.70). Our results demonstrate that the MF approach can model ranked inundation extent of known pond locations with results comparable to or better than LSMA, but further refinement is required for estimating absolute inundation areas and mapping wetlands <1 Landsat pixel.

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Acknowledgements

We thank Caren Goldberg for providing GPS locations of sampling sites and K. Stemp for acquiring satellite imagery. We also thank W. Lowe, T. Wilcox, B. Addis, R. Kovach, P. Garciasoto, M. Bayer, L. Joyce, and three anonymous reviewers for their comments that improved the manuscript. Funding was provided by the USGS Amphibian Research and Monitoring Initiative (ARMI) and the USGS Environments Program. This manuscript is ARMI contribution no. 698. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

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Authors and Affiliations

  1. Biosystems Engineering, University of Arizona, 1177 E. 4th St., Tucson, AZ, 85719, USA

    Christopher J. Jarchow

  2. U.S. Geological Survey, Southwest Biological Science Center, University of Arizona, 520 N. Park Avenue, Tucson, AZ, 85719, USA

    Brent H. Sigafus

  3. U.S. Geological Survey, Fort Collins Science Center, 2150 Center Ave. Bldg. C, Fort Collins, CO, 80526, USA

    Erin Muths

  4. U.S. Geological Survey, Northern Rocky Mountain Science Center, 800 E. Beckwith Ave., Missoula, MT, 59801, USA

    Blake R. Hossack

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  1. Christopher J. Jarchow
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Correspondence to Christopher J. Jarchow.

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Jarchow, C.J., Sigafus, B.H., Muths, E. et al. Using Full and Partial Unmixing Algorithms to Estimate the Inundation Extent of Small, Isolated Stock Ponds in an Arid Landscape. Wetlands 40, 563–575 (2020). https://doi.org/10.1007/s13157-019-01201-7

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